In this keynote analysis from Workiva Amplify 2026 in Las Vegas, theCUBE's Krista Case and Alison Kosik break down the themes from Workiva CEO Julie Iskow's keynote address, exploring how trust and connected data are shaping the agentic AI era. Case highlights how Workiva Chief Product Officer Deepak Bharadwaj's product demo tackled a core tension: AI is inherently probabilistic, yet compliance and reporting demand deterministic, defensible outcomes. She explains why traceability is becoming the foundation for trusting AI-generated work product, especially as organizations ask AI agents to execute regulated tasks rather than simply assist with them.

The conversation also explores Workiva's evolving role as connective tissue across disparate systems, from ERPs to spreadsheets to institutional knowledge held by individual employees. Case notes how the company is extending beyond its roots in financial reporting into sustainability, risk and compliance, capturing greater share of wallet within existing accounts. Using Iskow's own keynote example — a $5.3 billion figure with no context about what it represents or who owns it — the hosts underscore why numbers alone are meaningless without traceable context behind them. Case frames trust as a two-part challenge: verifying the underlying data itself, then verifying that an AI agent's decision-making, such as compiling a 10-K filing, is auditable and grounded in industry and regulatory understanding. The analysis sets the stage for a full day of Amplify interviews digging deeper into these themes.

In this interview from Amplify 2026, Deepak Bharadwaj, executive vice president and chief product officer at Workiva, joins theCUBE's Krista Case and Alison Kosik to discuss why trust, not just speed, is the defining requirement for AI agents in financial reporting, audit and compliance. Bharadwaj explains that agents must operate on certified, governed data while producing traceable, audit-ready output. He details how Workiva Knowledge grounds agents in company-specific context and policies, while guardrails and human checkpoints determine where judgment-based tasks — like drafting a disclosure — require human sign-off versus rules-based tasks such as rolling forward filings. He underscores that accountability ultimately rests with people, not agents.

The conversation also explores the newly announced Agent Studio, which lets business users build their own agents without technical skills, extending Workiva's platform beyond what any single vendor could build alone. Bharadwaj breaks down multi-agent orchestration, explaining how permission-enforced capabilities and human checkpoints keep swarms of agents under a governed umbrella. He highlights how structuring unstructured evidence, such as invoices and purchase orders, lets audit teams expand testing coverage without adding headcount, freeing auditors to focus on remediation and judgment. Bharadwaj describes a "layers of Swiss cheese" approach, where combining AI and human review compounds trust across the process. He closes by outlining how customer feedback and rapidly evolving LLM capabilities steer Workiva's roadmap, distinguishing companies that solve real user problems with AI from those chasing AI for its own sake.

In this interview from Amplify 2026, Keri Tracy, vice president and chief audit executive at Newell Brands, joins theCUBE's Krista Case and Alison Kosik to discuss how internal audit is evolving from a governance checkpoint into a strategic partner for AI transformation. Tracy details Newell's "lean before AI" philosophy, emphasizing process optimization before layering automation on top. She explains how audit earned a seat at the table for the company's Quantum Leap initiative, spanning more than 100 AI projects, by calibrating speed to risk — moving fast on low-risk use cases like customer service agents while slowing down for higher-stakes areas like fixed asset accounting.

The conversation also explores how AI is compressing the audit cycle, with Tracy pushing her team toward a two-week turnaround inspired by PwC's ambition for a 24-hour audit. She highlights how predictive, exception-based testing is replacing random sampling, allowing auditors to analyze the full population of transactions and flag outliers with greater precision. Tracy also reflects on Workiva's cross-platform AI agents, which connect SEC reporting, SOX, ERM and audit systems into a more unified view. As autonomous agents increasingly interact with one another, she notes the risk profile itself is shifting toward governing AI's behavior rather than just human error. From psychological safety to involving IT early in transformation planning, Tracy underscores that change management — not technology alone — determines whether AI initiatives succeed.